Abstract
Introduction
We used next-generation, state-of-the-art, culture-independent methodology to survey urine microbiota of UCPPS males and control participants enrolled in the MAPP Network to investigate a possible microbial etiology.
Methods
Male UCPPS patients and matched controls were asked to provide VB1, VB2 and VB3 urine specimens. Specimens were analyzed with Ibis T-5000 Universal Biosensor technology to provide comprehensive identification of bacterial and select fungal species. Differences between UCPPS and control study participants for presence of species or species variation within a higher taxonomic grouping (genus) were evaluated using permutational multivariate analysis of variance and logistic regression.
Results
VB1 and VB2 urine specimens were obtained from 110 (VB3 in 67) UCPPS participants and 115 (VB3 in 62) controls. A total of 78, 73 and 54 species (42, 39 and 27 genera) were detected in VB1, VB2 and VB3 respectively. Mean (SD) VB1, VB2 and VB3 species count per person was 1.62 (1.28), 1.38 (1.36) and 1.33(1.24) for cases and 1.75(1.32), 1.23(1.15) and 1.56 (0.97) for controls respectively. Overall species and genus composition differed significantly between UCPPS and control participants in VB1 (p=0.002 species level, p=0.004 genus level) with Burkholderia cenocepacia over represented in UCPPS cases. No significant differences were observed at any level in VB2 or VB3 samples.
Conclusions
Assessment of baseline culture-independent microbiological data from male subjects enrolled in the MAPP Network has identified over representation of B cenocepacia in UCPPS. Future studies are planned to further evaluate microbiota associations with variable and changing UCPPS symptom patterns.
Keywords: Microbiome, Infection, Chronic Prostatitis, Chronic Pelvic Pain Sydrome
INTRODUCTION
Chronic prostatitis was traditionally considered an infectious disease of bacterial origin and for decades treated primarily with antibiotics1. In contrast, CP/CPPS and IC/BPS diagnosed in men, collectively referred to as male Urologic Chronic Pelvic Pain Syndrome (UCPPS), have been defined by the absence of identifiable bacterial infection as a cause for the chronic pain and urinary symptoms. The microbiologic diagnosis of infection in the prostate has traditionally been based upon the use of cultivation techniques in which bacteria are isolated from voided urine or EPS on specific nutritive media and under environmental conditions that only support growth for certain species. However, the vast majority of bacteria resist such cultivation and most chronic bacterial infections are nearly universally associated with a biofilm mode of growth2,3 that is highly recalcitrant to antibiotic therapy and difficult to culture. Bacterial biofilms have been identified in culture-negative patients with a past history of chronic bacterial prostatitis who had become refractory to antibiotics4.5. Molecular techniques, that do not rely on bacterial growth in vitro, including molecular-phylogenetic approaches based on ribosomal RNA gene sequences (16S RNA PCR techniques)6 have resulted in conflicting conclusions regarding the contributions of infectious agents in UCPPS7-14.
The objective of this study was to utilize a novel, state-of-the-art, culture-independent method to characterize the microbiota of male UCPPS and control (i.e. no UCPPS related symptoms) study participants recruited within the MAPP Network EP Study15,16 and to analyze microbiome differences relative to the extensive associated clinical data collected in that study. We employed the next-generation molecular diagnostic Ibis T-5000 Universal Biosensor technology17 which provides universal and comprehensive identification of all bacterial species present at >1-3% of the microbiome. The use of this advanced technology in combination with highly detailed clinical data from a large number of UCPPS patients and matched controls provides the MAPP Research Network an unparalleled opportunity to perform discovery analyses and test hypotheses relating to the contribution of the microbiome as an etiology for male UCPPS.
METHODS
Participants and Specimens
The Trans-MAPP EP Study recruited UCPPS participants for baseline phenotyping and longitudinal follow-up of the treated history of UCPPS symptoms, with standardized data acquisition and analysis and biological sample collection across network sites. In addition, the study enrolled positive controls (individuals with non-urologically associated chronic pain syndromes), and age/sex matched healthy controls for the same baseline phenotyping assessments15,16.
Inclusion criteria for UCPPS study participants for the MAPP EP Study included: 1) a diagnosis of IC/BPS or CP/CPPS, with urologic symptoms present a majority of the time during any 3 of the past 6 months (CP/CPPS) or the most recent 3 months (IC/BPS); 2) at least 18 years old; 3) reporting a non-zero score for bladder/prostate and/or pelvic region pain, pressure or discomfort during the past 2 weeks; and 4) appropriate consent. Exclusion criteria have been described 15. Healthy controls were recruited to be age- and sex-matched to UCPPS patients, and positive controls were defined as subjects meeting criteria for the non-urological associated syndromes, primarily fibromyalgia, chronic fatigue syndrome, and/or irritable bowel syndrome. Further details of the study design, including descriptions of the study population enrollment criteria and disease specific questionnaires are available15.
The current study details data collected from male participants who provided both initial stream urine (VB1) and midstream urine (VB2) specimens. A reduced number of case and control subjects were able to provide a post-prostate massage urine (VB3) specimen. Patients with a positive urine culture (traditional uropathogen isolated in VB2 employing traditional culture technique) at baseline or within last 6 weeks were excluded from analysis.
Specimen handling
After collection of urine specimens (20 ml volumes collected after initial saline wipe of glans) using standardized collection kits at MAPP Network Discovery sites, specimens were transferred to 50 mL conical tubes and frozen at −80 oC until shipping to central MAPP Network Tissue Analysis and Technology Core (TATC). Specimens were then thawed, thoroughly mixed, and aliquoted into 1 and 3 mL aliquots and refrozen at −80 oC until use. Three mL frozen aliquots were transferred to the Center for Genomic Sciences in Pittsburgh for microbial analyses.
Ibis T-5000 Universal Biosensor Analysis: DNA extraction and Ibis eubacterial and fungal domain assays
In brief, total DNA was extracted from all urine samples, and microbial (i.e., bacterial and fungal) DNAs were amplified by the polymerase chain reaction (PCR) using the 16 primer pair BAC (Bacteria, antibiotic resistance genes and Candida) and Fungal detection systems developed by Ibis as described17. The individual amplicons were “weighed” using the Ibis instrumentation by electrospray ionization (ESI) time-of-flight (TOF) mass spectrometer (MS) which reports out the molecular mass. The amplicon masses are then used to determine their base compositions as a particular mass can only be produced by a single combination of the four nucleotides (A, C, G, & T). The taxonomic identities of the amplicons were then revealed using a database containing base composition data on virtually all bacterial/fungal species sequenced to date. Details of the methodology are available in Appendix 2.
Statistical Analysis
Demographic characteristics and relevant clinical features were compared between male UCPPS and control participants by Chi-Square tests. Differences in the overall microbial composition for UCPPS males versus control males were assessed by permutational multivariate analysis (PERMANOVA)18. This procedure is a nonparametric analogue of multivariate ANOVA that uses resampling for inference. The presence or absence of particular taxa for each subject is converted into a numerical matrix from which distance matrices are calculated and compared between groups according to a selected distance measure. The Euclidean distance was chosen as the basis of this analysis. Differences in the representation of individual taxa were tested using logistic regression for the presence or absence and PERMANOVA for differences in species richness within a higher level classification such as genus or Gram-Stain. All testing was conducted at the species, genus, and Gram-stain level. At the genus and Gram-stain levels, the primary test considered differences in species richness, but inference for differences in the presence or absence of a group within a level are also presented. Tests of individual taxa were adjusted for multiple comparisons by controlling the false discovery rate (FDR)19. Models adjusted for potential confounding by the demographic variables of age, race, and employment.
RESULTS
VB1 (urethral) and VB2 (bladder) urine specimens were obtained from 110 male UCPPS participants and 115 age and sex matched healthy and positive controls at their MAPP EP Study baseline assessment. VB3 samples (containing variable amount of EPS) were also collected from 67 UCPPS and 62 control participants. Baseline demographic data are shown in Table 1 (VB1/2) and Table 2 (VB3). There was no significant difference in race or ethnicity between UCPPS and control groups, however, minor differences were noted in age, employment and income between UCPPS participants and controls. In men with UCPPS who provided both VB1 and VB2 specimens, 86% reported a previous diagnosis of CP, whereas 20% reported a previous diagnosis of IC (Table 3); similar proportions of CP and IC diagnoses were also reported by UCPPS participants providing all 3 specimens (Table 4). All male UCPPS participants assessed met a clinically defined CP/CPPS diagnostic criteria (i.e., reported pain or discomfort in any of the 8 domains of the Male Genitourinary Pain Index (GUPI)15 during any 3 months in the previous 6 months) while 69 - 71.6% met a clinically defined IC/BPS diagnostic criteria (i.e., unpleasant sensation of pain, pressure, or discomfort, perceived to be related to the bladder and/or pelvic region, associated with lower urinary tract symptoms in the most recent 3 months). The mean (SD) chronic prostatitis symptom score (CPSI) was 22.1 (8.3) and 2.5 (4.2) for VB1/2 UCPPS and control participants, respectively; 20.9 (7.6) and 1.8 (2.6) for VB3 UCPPS and control participants, respectively. The mean (SD) male GUPI scores were 24.2 (9.0) and 2.5 (4.5) for VB1/2 UCPPS and control participants, respectively; 23.1 (8.4) and 1.8 (2.6) for VB3 UCPPS and control participants, respectively (Tables 3 and 4).
Table 1.
Baseline demographics for subjects who provided VB1 and VB2 urine specimens.
| Category | UCPPS | Controls | Total | p | |
|---|---|---|---|---|---|
| Number of Participants | N (%) | 110 | 115 | 225 | |
| Age Group | <35 years | 23 (20.9%) | 39 (33.9%) | 62 (27.6%) | 0.038 |
| 35-50 Years | 37 (33.6%) | 40 (34.8%) | 77 (34.2%) | ||
| 50+ Years | 50 (45.5%) | 36 (31.3%) | 86 (38.2%) | ||
| Race | White | 102 (92.7%) | 97 (84.3%) | 199 (88.4%) | 0.147 |
| Black | 4 (3.6%) | 5 (4.3%) | 9 (4.0%) | ||
| Asian | 3 (2.7%) | 4 (3.5%) | 7 (3.1%) | ||
| Multi Race | 4 (3.5%) | 4 (1.8%) | |||
| Other | 1 (0.9%) | 5 (4.3%) | 6 (2.7%) | ||
| Ethnicity | Hispanic | 6 (5.5%) | 6 (5.2%) | 12 (5.3%) | 1.000 |
| Non-Hispanic | 103 (93.6%) | 109 (94.8%) | 212 (94.2%) | ||
| Unknown | 1 (0.9%) | 1 (0.4%) | |||
| Employment | Employed | 74 (67.3%) | 73 (63.5%) | 147 (65.3%) | 0.007 |
| Unemployed | 8 (7.3%) | 24 (20.9%) | 32 (14.2%) | ||
| Retired | 21 (19.1%) | 13 (11.3%) | 34 (15.1%) | ||
| Full-time homemaker | 2 (1.7%) | 2 (0.9%) | |||
| Disabled | 7 (6.4%) | 3 (2.6%) | 10 (4.4%) | ||
| Income (Annual) | $10,000 or less | 6 (5.5%) | 10 (8.7%) | 16 (7.1%) | 0.002 |
| $10,001 to $25,000 | 6 (5.5%) | 20 (17.4%) | 26 (11.6%) | ||
| $25,001 to $50,000 | 17 (15.5%) | 22 (19.1%) | 39 (17.3%) | ||
| $50,001 to $100,000 | 34 (30.9%) | 36 (31.3%) | 70 (31.1%) | ||
| More than $100,000 | 39 (35.5%) | 18 (15.7%) | 57 (25.3%) | ||
| Prefer not to Answer | 7 (6.4%) | 9 (7.8%) | 16 (7.1%) | ||
| Missing | 1 (0.9%) | 1 (0.4%) |
Table 2.
Baseline data for subjects who were able to provide all three urine specimens (VB1, VB2, and VB3).
| Category | UCPPS | Controls | Total | p | |
|---|---|---|---|---|---|
| Number of Participants | N (%) | 67 | 62 | 129 | |
| Age Group | <35 years | 12 (17.9%) | 17 (27.4%) | 29 (22.5%) | 0.452 |
| 35-50 Years | 20 (29.9%) | 17 (27.4%) | 37 (28.7%) | ||
| 50+ Years | 35 (52.2%) | 28 (45.2%) | 63 (48.8%) | ||
| Race | White | 65 (97.0%) | 55 (88.7%) | 120 (93.0%) | 0.081 |
| Black | 3 (4.8%) | 3 (2.3%) | |||
| Asian | 2 (3.0%) | 1 (1.6%) | 3 (2.3%) | ||
| Multi Race | 2 (3.2%) | 2 (1.6%) | |||
| Other | 1 (1.6%) | 1 (0.8%) | |||
| Ethnicity | Hispanic | 3 (4.8%) | 3 (2.3%) | 0.111 | |
| Non-Hispanic | 66 (98.5%) | 59 (95.2%) | 125 (96.9%) | ||
| Unknown | 1 (1.5%) | 1 (0.8%) | |||
| Employment | Employed | 43 (64.2%) | 37 (59.7%) | 80 (62.0%) | 0.275 |
| Unemployed | 4 (6.0%) | 10 (16.1%) | 14 (10.9%) | ||
| Retired | 15 (22.4%) | 11 (17.7%) | 26 (20.2%) | ||
| Full-time homemaker | 1 (1.6%) | 1 (0.8%) | |||
| Disabled | 5 (7.5%) | 3 (4.8%) | 8 (6.2%) | ||
| Income | $10,000 or less | 3 (4.5%) | 7 (11.3%) | 10 (7.8%) | 0.002 |
| $10,001 to $25,000 | 3 (4.5%) | 12 (19.4%) | 15 (11.6%) | ||
| $25,001 to $50,000 | 11 (16.4%) | 10 (16.1%) | 21 (16.3%) | ||
| $50,001 to $100,000 | 19 (28.4%) | 22 (35.5%) | 41 (31.8%) | ||
| More than $100,000 | 27 (40.3%) | 9 (14.5%) | 36 (27.9%) | ||
| Prefer not to Answer | 3 (4.5%) | 2 (3.2%) | 5 (3.9%) | ||
| Missing | 1 (1.5%) | 1 (0.8%) |
Table 3.
Disease specific characteristics for subjects who provided VB1 and VB2 urine specimens
| Category | UCPPS | Controls | Total | p | |
|---|---|---|---|---|---|
| Number of Participants | N (%) | 110 | 115 | 225 | |
| Self-reported IC diagnosis | No | 88 (80.0%) | 109 (94.8%) | 197 (87.6%) | <.001 |
| Yes | 22 (20.0%) | 22 (9.8%) | |||
| Missing | 6 (5.2%) | 6 (2.7%) | |||
| Self-reported CP diagnosis | No | 24 (21.8%) | 109 (94.8%) | 133 (59.1%) | <.001 |
| Yes | 86 (78.2%) | 86 (38.2%) | |||
| Missing | 6 (5.2%) | 6 (2.7%) | |||
| Meet IC/PBS Criteria (see text) | No | 34 (30.9%) | 34 (15.1%) | ||
| Yes | 76 (69.1%) | 76 (33.8%) | |||
| Missing | 115 (100.0%) | 115 (51.1%) | |||
| Meets CP/CPPS Criteria (see text) | Yes | 110 (100.0%) | 110 (48.9%) | ||
| Missing | 115 (100.0%) | 115 (51.1%) | |||
| Mean CPSI (SD) | 22.1 (8.3) | 2.5 (4.2) | 12.0 (11.8) | <.001 | |
| Mean male GUPI (SD) | 24.2 (9.0) | 2.5 (4.5) | 13.1 (13.0) | <.001 | |
| Meds for urologic or pelvic pain symptoms | No | 36 (32.7%) | 113 (98.3%) | 149 (66.2%) | <.001 |
| Yes | 74 (67.3%) | 2 (1.7%) | 76 (33.8%) | ||
| Pain medication class | None | 39 (35.5%) | 89 (77.4%) | 128 (56.9%) | <.001 |
| Peripheral | 12 (10.9%) | 15 (13.0%) | 27 (12.0%) | ||
| Central | 49 (44.5%) | 11 (9.6%) | 60 (26.7%) | ||
| Opioid | 10 (9.1%) | 10 (4.4%) |
Table 4.
Disease specific characteristics for subjects who were able to provide all three urine specimens (VB1, VB2, and VB3).
| Category | UCPPS | Controls | Total | p | |
|---|---|---|---|---|---|
| Number of Participants | N (%) | 67 | 62 | 129 | |
| Self-reported IC diagnosis | No | 54 (80.6%) | 56 (90.3%) | 110 (85.3%) | <.001 |
| Yes | 13 (19.4%) | 13 (10.1%) | |||
| Missing | 6 (9.7%) | 6 (4.7%) | |||
| Self-reported CP diagnosis | No | 18 (26.9%) | 56 (90.3%) | 74 (57.4%) | <.001 |
| Yes | 49 (73.1%) | 49 (38.0%) | |||
| Missing | 6 (9.7%) | 6 (4.7%) | |||
| Meet IC/PBS Criteria (see text) | No | 19 (28.4%) | 19 (14.7%) | ||
| Yes | 48 (71.6%) | 48 (37.2%) | |||
| Missing | 62 (100.0%) | 62 (48.1%) | |||
| Meets CP/CPPS Criteria (see text) | Yes | 67 (100.0%) | 67 (51.9%) | ||
| Missing | 62 (100.0%) | 62 (48.1%) | |||
| Mean CPSI (SD) score | 20.9 (7.6) | 1.8 (2.6) | 11.7 (11.2) | <.001 | |
| Mean male GUPI Total (SD) score | 23.1 (8.4) | 1.8 (2.6) | 12.9 (12.4) | <.001 | |
| Meds for urologic or pelvic pain symptoms | No | 17 (25.4%) | 61 (98.4%) | 78 (60.5%) | <.001 |
| Yes | 50 (74.6%) | 1 (1.6%) | 51 (39.5%) | ||
| Pain medication class | None | 21 (31.3%) | 45 (72.6%) | 66 (51.2%) | <.001 |
| Peripheral | 6 (9.0%) | 10 (16.1%) | 16 (12.4%) | ||
| Central | 33 (49.3%) | 7 (11.3%) | 40 (31.0%) | ||
| Opioid | 7 (10.4%) | 7 (5.4%) |
Analysis of urine samples revealed a total of 78 species (42 genera) in VB1 while VB2 and VB3 samples were shown to contain a total of 73 (39 genera) and 54 species (27 genera), respectively. Mean (SD) VB1 species count per person was 1.62 (1.28) and 1.75 (1.32) for UCPPS and control participants, respectively. Mean VB2 species count per person was 1.38 (1.36) and 1.23 (1.15) among UCPPS and control participants, respectively. Among VB3 samples mean (SD) species count per person was 1.33(1.24) and 1.56(0.97) for UCPPS and control participant, respectively
Overall genus and species composition significantly differed between UCPPS and control participants in VB1 samples (p=0.002 species level, p=0.004 genus level, p=0.027 Gram-stain level). Examining individual species, the overall difference was driven by Burkholderia cenocepacia, Propionibacterium acnes, and Staphylococcus capitis/caprae. Only B. cenocepacia was overrepresented in UCPPS (Adjusted OR=1.9, p=0.0159), (Table 5a). Prompted by the finding that comparison of species in VB1 appeared to show the most robust differences between groups, a representative VB1 species cluster analysis was conducting based on Euclidean distances and hierarchical clustering with complete linkage (Figure 1). Similar trends were observed at the genus level with significance retained after FDR adjustment. At the Gram-stain level, overall difference in composition was also detected in VB1, driven by differences in the prevalence of Gram-positive and Gram-negative species. No significant differences in overall composition or prevalence of individual species at the Gram-stain level were observed in VB2 or VB3 (Table 5b,c). Fifty-one species (26 genera) were present in individual participants’ VB3 but not in their respective VB1 or 2 samples. However, only one species and two genera were noted in more than 10 subjects (no fungal species or genera were noted in more than 10 subjects) and the difference between UCPPS and control participants were not significant (Table 5d), suggesting these microbes may not have a major contribution to UCPPS pathophysiology. Uropathogenic bacteria were identified in 8.7% of control vs 5.5% of UCPPS participants in VB1; 5.2% of controls vs 11.8% of UCPPS participants in VB2; 6.5% of controls vs 4.5% of UCPPS participants in VB3 (Table 6). However, only five uropathogens were localized to VB3 (i.e., VB3 but not VB1 and/or VB2) in subjects who provided all three specimens; three (4.8%) control group and two (3%) UCPPS participants (Table 6).
Table 5A.
Differences in Species Composition in VB1 (only taxa present in at least 10 subjects were tested individually)
| VB1 | Controls N (%) |
UCPPS N (%) |
p unadjusted (richness) |
p unadjusted (presence/ absence) |
p adjusted (richness) |
p adjusted (presence/ absence) |
|---|---|---|---|---|---|---|
| Number of Participants | 115 | 110 | ||||
| Species + | 0.004 | 0.002 | ||||
| Bifidobacterium subtile | 9 (7.8%) | 6 (5.5%) | 0.4782 | 0.6718 | ||
| Burkholderia cenocepacia+ | 5 (4.3%) | 16 (14.5%) | 0.0129 | 0.0159 | ||
| Finegoldia magna | 11 (9.6%) | 9 (8.2%) | 0.7157 | 0.4784 | ||
| Listeria innocua/monocytogenes | 5 (4.3%) | 5 (4.5%) | 0.9427 | 0.9473 | ||
| Propionibacterium acnes+ | 19 (16.5%) | 7 (6.4%) | 0.0213 | 0.0097 | ||
| Staphylococcus capitis/caprae+ | 12 (10.4%) | 2 (1.8%) | 0.0178 | 0.0107 | ||
| Staphylococcus epidermidis/haemolyticus |
38 (33%) | 28 (25.5%) | 0.2124 | 0.0781 | ||
| Staphylococcus hominis | 23 (20%) | 14 (12.7%) | 0.1441 | 0.1074 | ||
| Streptococcus agalactiae | 9 (7.8%) | 5 (4.5%) | 0.3141 | 0.2483 | ||
| Streptococcus parasanguinis/pneumoniae |
7 (6.1%) | 13 (11.8%) | 0.1376 | 0.1199 | ||
| Genus + | 0.013 | 0.02 | 0.004 | 0.006 | ||
| Bifidobacterium | 9 (7.8%) | 7 (6.4%) | 0.628 | 0.6701 | 0.74 | 0.8496 |
| Burkholderia+* | 5 (4.3%) | 16 (14.5%) | 0.015 | 0.0129 | 0.007 | 0.0159 |
| Finegoldia | 11 (9.6%) | 9 (8.2%) | 0.814 | 0.7157 | 0.476 | 0.4784 |
| Lactobacillus | 6 (5.2%) | 11 (10%) | 0.171 | 0.1819 | 0.116 | 0.1028 |
| Listeria | 5 (4.3%) | 6 (5.5%) | 0.787 | 0.7009 | 0.82 | 0.816 |
| Propionibacterium+* | 19 (16.5%) | 7 (6.4%) | 0.024 | 0.0213 | 0.006 | 0.0097 |
| Staphylococcus+* | 60 (52.2%) | 44 (40%) | 0.02 | 0.0678 | 0.005 | 0.0164 |
| Streptococcus | 21 (18.3%) | 24 (21.8%) | 0.904 | 0.5053 | 0.943 | 0.5008 |
| Gram Stain + | 0.087 | 0.12 | 0.027 | 0.083 | ||
| Gram negative+* | 22 (19.1%) | 34 (30.9%) | 0.066 | 0.0426 | 0.041 | 0.0267 |
| Gram positive+* | 85 (73.9%) | 78 (70.9%) | 0.095 | 0.6143 | 0.039 | 0.5671 |
Significant at the 0.05 level in adjusted analysis
Significant under FDR of 0.05 for multiple comparisons in adjusted analysis
Figure 1.
VB1 Species Cluster Analysis by Cohort. light blue – Controls; dark; blue - UCPPS
Table 5B.
Differences in Species Composition in VB2 (only taxa present in at least 10 subjects were tested individually)
| VB2 | Controls N (%) |
UCPPS N (%) |
p unadjusted (richness) |
p unadjusted (presence/ absence) |
p adjusted (richness) |
p adjusted (presence/ absence) |
|---|---|---|---|---|---|---|
| Overall | 115 | 110 | ||||
| Species | 0.354 | 0.477 | ||||
| Enterococcus faecalis | 5 (4.3%) | 5 (4.5%) | 0.9427 | 0.9838 | ||
| Propionibacterium acnes | 14 (12.2%) | 6 (5.5%) | 0.0842 | 0.0533 | ||
| Staphylococcus capitis/caprae | 4 (3.5%) | 6 (5.5%) | 0.4757 | 0.7136 | ||
| Staphylococcus epidermidis/haemolyticus |
28 (24.3%) | 30 (27.3%) | 0.6162 | 0.927 | ||
| Staphylococcus hominis | 12 (10.4%) | 11 (10%) | 0.9143 | 0.9269 | ||
| Streptococcus parasanguinis/pneumoniae |
4 (3.5%) | 6 (5.5%) | 0.4757 | 0.8238 | ||
| Genus | 0.238 | 0.227 | 0.380 | 0.370 | ||
| Bifidobacterium | 7 (6.1%) | 3 (2.7%) | 0.282 | 0.2335 | 0.472 | 0.4757 |
| Enterococcus | 5 (4.3%) | 5 (4.5%) | 1 | 0.9427 | 0.988 | 0.9838 |
| Lactobacillus | 9 (7.8%) | 10 (9.1%) | 0.451 | 0.7333 | 0.249 | 0.4739 |
| Listeria | 3 (2.6%) | 7 (6.4%) | 0.207 | 0.1856 | 0.263 | 0.2562 |
| Propionibacterium+ | 14 (12.2%) | 6 (5.5%) | 0.108 | 0.0842 | 0.046 | 0.0533 |
| Staphylococcus | 47 (40.9%) | 52 (47.3%) | 0.307 | 0.3338 | 0.539 | 0.7397 |
| Streptococcus | 11 (9.6%) | 8 (7.3%) | 1 | 0.5376 | 0.62 | 0.2818 |
| Gram Stain | 0.426 | 0.762 | 0.724 | 0.935 | ||
| Gram negative | 19 (16.5%) | 21 (19.1%) | 0.644 | 0.6146 | 0.554 | 0.6911 |
| Gram positive | 67 (58.3%) | 68 (61.8%) | 0.405 | 0.5862 | 0.673 | 0.9603 |
Significant at the 0.05 level in adjusted analysis
Significant under FDR of 0.05 for multiple comparisons in adjusted analysis
Table 5C.
Differences in Species Composition in VB3 (only taxa present in at least 10 subjects were tested individually)
| VB3 | Controls N (%) |
UCPPS N (%) |
p unadjusted (richness) |
p unadjusted (presence/ absence) |
p adjusted (richness) |
p adjusted (presence/ absence) |
|---|---|---|---|---|---|---|
| Overall | 62 | 67 | ||||
| Species | 0.82 | 0.804 | ||||
| Listeria innocua/monocytogenes | 6 (9.7%) | 4 (6%) | 0.4356 | 0.698 | ||
| Propionibacterium acnes | 5 (8.1%) | 5 (7.5%) | 0.8984 | 0.6228 | ||
| Staphylococcus epidermidis/haemolyticus |
20 (32.3%) | 18 (26.9%) | 0.5025 | 0.4159 | ||
| Staphylococcus hominis | 6 (9.7%) | 8 (11.9%) | 0.6802 | 0.5491 | ||
| Genus | 0.433 | 0.613 | 0.332 | 0.592 | ||
| Lactobacillus | 7 (11.3%) | 7 (10.4%) | 0.843 | 0.8779 | 0.878 | 0.8185 |
| Listeria | 6 (9.7%) | 4 (6%) | 0.52 | 0.4356 | 0.731 | 0.698 |
| Propionibacterium | 5 (8.1%) | 5 (7.5%) | 1 | 0.8984 | 0.628 | 0.6228 |
| Staphylococcus | 36 (58.1%) | 32 (47.8%) | 0.196 | 0.2424 | 0.11 | 0.194 |
| Streptococcus | 8 (12.9%) | 8 (11.9%) | 0.822 | 0.8684 | 0.894 | 0.7573 |
| Gram Stain | 0.523 | 0.099 | 0.448 | 0.078 | ||
| Gram negative | 13 (21%) | 7 (10.4%) | 0.191 | 0.105 | 0.269 | 0.1513 |
| Gram positive | 49 (79%) | 45 (67.2%) | 0.603 | 0.1324 | 0.446 | 0.0881 |
Significant at the 0.05 level in adjusted analysis
Significant under FDR of 0.05 for multiple comparisons in adjusted analysis
Table 5D.
Differences in Species Composition in VB3 not VB1 or VB2 (only taxa present in at least 10 subjects were tested individually)
| VB3 not VB1 or VB2 | Controls N (%) |
UCPPS N (%) |
p unadjusted (richness) |
p unadjusted (presence/ absence) |
p adjusted (richness) |
p adjusted (presence/ absence) |
|---|---|---|---|---|---|---|
| Overall | 62 | 67 | ||||
| Species | 0.376 | 0.510 | ||||
| Staphylococcus epidermidis/haemolyticus |
7 (11.3%) | 6 (9%) | 0.6604 | 0.7298 | ||
| Genus | 0.223 | 0.24 | 0.224 | 0.245 | ||
| Staphylococcus | 23 (37.1%) | 18 (26.9%) | 0.152 | 0.2139 | 0.154 | 0.1878 |
| Streptococcus | 7 (11.3%) | 3 (4.5%) | 0.381 | 0.1619 | 0.274 | 0.1303 |
| Gram Stain | 0.28 | 0.187 | 0.325 | 0.292 | ||
| Gram negative | 12 (19.4%) | 5 (7.5%) | 0.128 | 0.0537 | 0.18 | 0.0883 |
| Gram positive | 35 (56.5%) | 33 (49.3%) | 0.463 | 0.4137 | 0.369 | 0.4241 |
Significant at the 0.05 level in adjusted analysis
Significant under FDR of 0.05 for multiple comparisons in adjusted analysis
Table 6.
Differences in Uropathogen Presence by cohort in VB1-VB3
| N (%) | Entero- bacter |
Entero- coccus |
Esche- richia |
Kleb- siella |
Proteus | Pseudo monas |
Any Uro- pathogen |
|
|---|---|---|---|---|---|---|---|---|
| VB1 | Controls (n=115) | 0 (0%) | 5 (4.3%) | 2 (1.7%) | 3 (2.6%) | 1 (0.9%) | 1 (0.9%) | 10 (8.7%) |
| UCPPS (n=110) | 1 (0.9%) | 3 (2.7%) | 2 (1.8%) | 1 (0.9%) | 0 (0%) | 0 (0%) | 6 (5.5%) | |
| p unadjusted | 0.9968 | 0.5154 | 0.9642 | 0.3567 | 0.9969 | 0.9969 | 0.3484 | |
| p adjusted | 0.9984 | 0.7121 | 0.9207 | 0.3238 | 0.9978 | 0.9985 | 0.5475 | |
| VB2 | Controls (n=115) | 0 (0%) | 5 (4.3%) | 0 (0%) | 1 (0.9%) | 0 (0%) | 0 (0%) | 6 (5.2%) |
| UCPPS (n=110) | 0 (0%) | 5 (4.5%) | 2 (1.8%) | 0 (0%) | 3 (2.7%) | 3 (2.7%) | 13 (11.8%) | |
| p unadjusted | 1 | 0.9427 | 0.9949 | 0.9969 | 0.9947 | 0.9947 | 0.0828 | |
| p adjusted | 1 | 0.9838 | 0.9976 | 0.9993 | 0.9965 | 0.9964 | 0.1045 | |
| VB3 | Controls (n=62) | 0 (0%) | 0 (0%) | 1 (1.6%) | 2 (3.2%) | 1 (1.6%) | 0 (0%) | 4 (6.5%) |
| UCPPS (n=67) | 0 (0%) | 1 (1.5%) | 1 (1.5%) | 0 (0%) | 0 (0%) | 1 (1.5%) | 3 (4.5%) | |
| p unadjusted | 1 | 0.9963 | 0.9559 | 0.9959 | 0.9961 | 0.9963 | 0.6228 | |
| p adjusted | 1 | 0.9974 | 0.8787 | 0.9981 | 0.9981 | 0.9982 | 0.7106 | |
|
VB3 not
1 or 2 |
Controls (n=62) | 0 (0%) | 0 (0%) | 0 (0%) | 2 (3.2%) | 1 (1.6%) | 0 (0%) | 3 (4.8%) |
| UCPPS (n=67) | 0 (0%) | 1 (1.5%) | 0 (0%) | 0 (0%) | 0 (0%) | 1 (1.5%) | 2 (3%) | |
| p unadjusted | 1 | 0.9963 | 1 | 0.9959 | 0.9961 | 0.9963 | 0.5893 | |
| p adjusted | 1 | 0.9974 | 1 | 0.9981 | 0.9981 | 0.9982 | 0.761 |
DISCUSSION
Earlier generation molecular diagnostic techniques employed to search for the presence of causative organisms in patients with negative urine cultures and a diagnosis of CP/CPPS, have produced contradictory results7-14. The Ibis T-5000 Universal Biosensor technology17 (see appendix 2 for details) employs a PCR-ESI-TOF MS coupled to a sophisticated dynamic relational database that is able to generate a definitive species-level diagnostic for all known bacterial species. In addition, the system provides a “most-closely-related match” for unknown organisms. This technology allows for a powerful discovery-based approach that is not subject to restrictions based on a priori assumptions of microbial profiles20,21.
The Trans-MAPP EP Study enrolled male UCPPS study participants who met the basic criteria of a defined CP/CPPS diagnosis, although only 86% self-reported a diagnosis of chronic prostatitis. Approximately 22% also self-reported a diagnosis of interstitial cystitis while 69% met the pre-defined criteria for IC/BPS. In this cohort of male UCPPS patients, we were not able to show a clear clinically significant difference in the microbiome (either individual microorganisms or groups of microorganisms) between UCPPS participants and control participants without UCPPS symptoms. We noted specific microbiome differences for Burkholderia cenocepacia (more prevalent in VB1 in UCPPS participants compared to controls) and others have described this organism as a pathogen22, possibly involved in the etiology of CP/CPPS23,24. The minor differences observed in VB1 for Propionibacterium acnes and Staphylococcus capitis/capare (both under represented in UCPPS participants compared to controls) may be clinically insignificant, but they could also indicate a change in the overall species balance.
No differences at the species, genus or gram stain level were detected between UCPPS and control participants for VB2 or VB3 samples. When we further analyzed those organisms presumed to be localized to VB3 through deletion of those also detected in VB1 and/or VB2 (similar to culture localization using the 3 glass test technique), we did not note any difference between UCPPS and control participants. Furthermore, examination of UCPPS participants identified with known uropathogenic bacteria in any specimen (as well as in VB3 localization), failed to show any clinically significant difference. A similar observation was previously noted in a traditional culture-based case/control cohort study25. Studies within the MAPP Network are currently in progress to correlate the presence of uropathogenic bacteria with inflammatory biomarker patterns (eg IL-6).
A number of limitations of our study should be noted. The fact that we did not identify any significant alterations in the microbiome of patients with a chronic urologic pain condition can not address the possibility that chronic inflammation and pain my persist after an offending organism has been cleared 26,27. We have also not ruled out the possibility that various organisms, particularly those localized to VB3, identified in UCPPS participants might influence various symptom changes (e.g., flare status) or are associated with select UCPPS patient subgroups (e.g., patients with differing symptom profiles, natural history, and/or underlying biological characteristics). Furthermore, this approach did not provide a comprehensive assessment of all fungal species or viruses. An additional limitation was that our specimens collected using standardized lower urinary tract collection methodology to enrich anatomical areas (urethra, bladder, prostate) would include mixed populations of microbes from all these areas as well as the kidney. The final caveat that remains with our approach is that we tested urine specimens which may or may not contain biofilm bacteria which in theory may only be detected if there is dispersion from the biofilm or mechanical disruption of the biofilm (in our study was only attempted by prostate massage). Our data is not sufficient to recommend empiric antimicrobial therapy for similar patients with CPPS. The strengths of our analyses lie in our use of the next generation Ibis T-5000 Universal Biosensor technology to accurately assess segmented urine microbiota in combination with comprehensive phenotyping of patients conducted in the MAPP EP Study. This allows for comparisons of microbial profiles to varied, complex clinical measures. The ambitious NIH funded Human Microbiome Project (HMP) recognizes the need to characterize microbial communities found at multiple human body sites and to look for correlations between changes in the microbiome in human health and disease28. Unfortunately there is a paucity of data for the urinary tract microbiome in health and disease [http://www.hmpdacc.org/]. Further analyses are planned in the MAPP Network to identify potential sub-groupings of UCPPS patients that may show significant difference in their urologic microbiome when stratified based on differing phenotypic characteristics, as well studies to correlate microbial profiles (including more comprehensive fungal survey) with symptom progression and change over time.
CONCLUSION
Assessment of baseline culture-independent microbiological data from male subjects enrolled in the MAPP Network study has identified B. cenocepacia as significantly increased in VB1 urine samples of UCPPS. Further work is needed to explore the microbial signature from mid stream urine and prostatic massage specimens in UCPPS men with variable and changing symptom patterns.
Supplementary Material
Acknowledgments
Source of Funding: National Institute of Diabetes and Digestive and Kidney Diseases (NIDDK), National Institutes of Health (NIH) MAPP Network Awards: U01DK82370, U01DK82342, U01DK82315, U01DK82344, U01DK82325, U01DK82345, U01DK82333, and U01DK82316.
Abbreviations
- CP
Chronic Prostatitis
- CP/CPPS
Chronic Prostatitis/Chronic Pelvic Pain Syndrome
- CPSI
Chronic Prostatitis Symptom Index
- EP
Epidemiological/Phenotyping
- EPS
Expressed Prostatic Secretion
- FDR
false discovery rate
- GUPI
Genitourinary Pain Index
- IC
Interstitial Cystitis
- IC/BPS
Interstitial Cystitis/Bladder Pain Syndrome
- MAPP
Multidisciplinary Approach to the study of Pelvic Pain
- MAPP-EP
Multidisciplinary Approach to the study of Pelvic Pain Epidemiological/Phenotyping study
- MS
mass spectroscopic
- PCR
polymerase chain reaction
- PCR-ESI-TOF MS
polymerase chain reaction –electron spray ionization – time-of-flight – mass spectroscopic
- TATC
Tissue Analysis and Technology Core
- UCPPS
Urologic Chronic Pelvic Pain Syndrome
- VB1
Voided Bladder 1 or initial stream urine (urethral) specimen
- VB2
Voided Bladder 2 or midstream urine (bladder) specimen
- VB3
Voided Bladder 3 or post prostatic massage urine (prostate) specimen
REFERENCES
- 1.Nickel JC. Prostatitis: An historical perspective. In: Nickel JC, editor. Textbook of Prostatitis. ISIS Medical Media Ltd.; Oxford: 1999. p. 3. [Google Scholar]
- 2.Costerton JW, Stewart PS, Greenberg EP. Bacterial biofilms: A common cause of persistent infections. Science. 1999;284:1318. doi: 10.1126/science.284.5418.1318. [DOI] [PubMed] [Google Scholar]
- 3.Wolcott RD, Ehrlich GD. Biofilms and Chronic Infections. JAMA. 2008;11:299. doi: 10.1001/jama.299.22.2682. [DOI] [PubMed] [Google Scholar]
- 4.Nickel JC, Costerton JW. Coagulase-negative staphylococcus in chronic prostatitis. J Urol. 1992;147:398. doi: 10.1016/s0022-5347(17)37247-6. 1992. [DOI] [PubMed] [Google Scholar]
- 5.Nickel JC, Costerton JW. Bacterial localization in antibiotic-refractory chronic bacterial prostatitis. The Prostate. 1993;23:107. doi: 10.1002/pros.2990230204. [DOI] [PubMed] [Google Scholar]
- 6.Ehrlich GD, Greenberg SJ. PCR-Based Diagnostics In Infectious Disease. Blackwell Scientific Publications; Boston: 1994. p. 697. [Google Scholar]
- 7.Tanner MA, Shoskes D, Shahed A, et al. Prevalence of corynebacterial 16S rRNA sequences in patients with bacterial and "nonbacterial" prostatitis. J Clin Microbiol. 1999;37:1863. doi: 10.1128/jcm.37.6.1863-1870.1999. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 8.Shoskes DA, Shahed AR. Detection of bacterial signal by 16S rRNA polymerase chain reaction in expressed prostatic secretions predicts response to antibiotic therapy in men with chronic pelvic pain syndrome. Tech Urol. 2000;6:240. [PubMed] [Google Scholar]
- 9.Krieger JN, Riley DE, Roberts MC, et al. Prokaryotic DNA sequences in patients with chronic idiopathic prostatitis. J Clin Microbiol. 1996;34:3120. doi: 10.1128/jcm.34.12.3120-3128.1996. 1996. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 10.Riley DE, Berger RE, Miner DC, et al. Diverse and related 16S rRNA-encoding DNA sequences in prostate tissues of men with chronic prostatitis. J Clin Microbiol. 36:1646–1652. doi: 10.1128/jcm.36.6.1646-1652.1998. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 11.Keay S, Zhang CO, Baldwin BR, et al. Polymerase chain reaction amplification of bacterial 16s rRNA genes in prostate biopsies from men without chronic prostatitis. Urol. 1999;53:487. doi: 10.1016/s0090-4295(98)00553-6. [DOI] [PubMed] [Google Scholar]
- 12.Hochreiter WW, Duncan JL, Schaeffer AJ. Evaluation of the bacterial flora of the prostate using a rRNA gene based polymerase chain reaction. J Urol. 2000;163:127. [PubMed] [Google Scholar]
- 13.Leskinen MJ, Rantakokko-Jalava K, et al. Negative bacterial polymerase chain reaction (PCR) findings in prostate tissue from patients with symptoms of chronic pelvic pain syndrome (CPPS) and localized prostate cancer. Prostate. 2003;55:105. doi: 10.1002/pros.10218. [DOI] [PubMed] [Google Scholar]
- 14.Xie H, Huang HC, Yang YR, et al. Detection of 16s ribosomal RNA gene of bacteria in prostate tissues of adults. Zhonghua Yi Xue Za Zhi. 2006;86:976. [PubMed] [Google Scholar]
- 15.Landis JR, Williams DA, Lucia MS, et al. The MAPP research network: design, patient characterization and operations. BMC Urology. 2014;14:58. doi: 10.1186/1471-2490-14-58. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 16.Clemens JQ, Mullins C, Kusek JW, et al. The MAPP research network: a novel study of urologic chronic pelvic pain syndromes. BMC Urology. 2014;14:57. doi: 10.1186/1471-2490-14-57. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 17.Ecker DJ, Sampath R, Massire C, et al. Ibis T5000: a universal biosensor approach for microbiology. Nat Rev Microbiol. 2008;6:553. doi: 10.1038/nrmicro1918. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 18.Yoav B, Hochberg Y. Controlling the false discovery rate: a practical and powerful approach to multiple testing. Journal of the Royal Statistical Society. Series B (Methodological) 1995:289–300. [Google Scholar]
- 19.Anderson MJ. A new method for non- parametric multivariate analysis of variance. Austral ecology. 2001;26:32. [Google Scholar]
- 20.Jacovides C, Kreft R, Adeli B, et al. Successful Identification of Pathogens by Polymerase Chain Reaction (PCR)-Based Electron Spray Ionization Time-of-Flight Mass Spectrometry (ESI-TOF-MS) in Culture-Negative Periprosthetic Joint Infection. Journal of Bone and Joint Surgery. 2012;94:2247. doi: 10.2106/JBJS.L.00210. [DOI] [PubMed] [Google Scholar]
- 21.Palmer MP, Altman D, Alman G, et al. Can We Trust Intraoperative Culture Results in Nonunions? J Orthop Trauma. 2014;28:384. doi: 10.1097/BOT.0000000000000043. [DOI] [PubMed] [Google Scholar]
- 22.Schwager S, Agnoli K, Köthe M, et al. Identification of Burkholderia cenocepacia strain H111 virulence factors using nonmammalian infection hosts. Infect Immun. 2013;81:143. doi: 10.1128/IAI.00768-12. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 23.Arzola JM, Hawley JS, Oakman C, Mora RV. A case of prostatitis due to Burkholderia pseudomallei. Nat Clin Pract Urol. 2007;4:111. doi: 10.1038/ncpuro0713. [DOI] [PubMed] [Google Scholar]
- 24.Organ Michael, Grantmyre John, Hutchinson Jim. Burkholderia cepacia infection of the prostate caused by inoculation of contaminated ultrasound gel during transrectal biopsy of the prostate. Can Urol Assoc J. 2010;4:E58. doi: 10.5489/cuaj.857. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 25.Nickel JC, Alexander RB, Schaeffer AJ, et al. Leukocytes and bacteria in men with chronic prostatitis/chronic pelvic pain syndrome compared to asymptomatic controls. J Urol. 2003;170:818. doi: 10.1097/01.ju.0000082252.49374.e9. [DOI] [PubMed] [Google Scholar]
- 26.Rudick CN, Berry RE, Johnson JR, et al. Uropathogenic Escherichia coli induces chronic pelvic pain. Infection and Immunity. 2011;79:628. doi: 10.1128/IAI.00910-10. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 27.Quick ML, Wong L, Mukherjee S, et al. Th1-Th17 Cells Contribute to the Development of Uropathogenic Escherichia coli-Induced Chronic Pelvic Pain. PLoS ONE. 2013;8:e60987. doi: 10.1371/journal.pone.0060987. [DOI] [PMC free article] [PubMed] [Google Scholar]
- 28.Aagaard K, Petrosino J, Keitel W, et al. The human microbiome project strategy for comprehensive sampling of the human microbiome and why it matters. J FASEB. 2013;27:1012. doi: 10.1096/fj.12-220806. [DOI] [PMC free article] [PubMed] [Google Scholar]
Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.